Current data search paradigms are quite good at performing trivial (level 0) correlation analyses, i.e., identifying records that contain matching terms. For example, if one searches the Internet for the string [“Joe Peterson” and “John Mitchell”], Google™, Bing™ Yahoo™ and other search engines find records that contain names of both individuals.
Level 1 correlations are much more difficult. For example, if both individuals attended UCLA, but there are no records containing both of their names, finding that correlation between the individuals could be challenging.
Level 2 and higher order correlations are even more difficult. For example, if Joe Peterson attended Stanford, where Mary Golden went to school, and Mary married John Mitchell, the correlation between Joe Peterson and John Mitchell would be extremely difficult to find using current search tools.
One of my earlier applications teaches use of concordances to facilitate searching in some circumstances, but that application does not contemplate successive (iterative) concordances. See US 2007/0219983 (Fish).
What is needed is computer systems, methods and models for assisting searchers in mining databases to identify Level 1 and higher order correlations.